Defillama_Backtester_v2_larry.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "78e893fc",
   "metadata": {},
   "source": [
    "---\n",
    "title: RToken Backtester \n",
    "description: Backtest RToken yields with Defillama historical data\n",
    "show-code: False\n",
    "params:\n",
    "    is_custom_weights:\n",
    "        label: Use custom basket weights (default is income-weighted)\n",
    "        input: checkbox\n",
    "        value: False    \n",
    "    basket_weights:\n",
    "        input: text\n",
    "        label: Basket weights (comma-separated as %)\n",
    "    basket_tokens:\n",
    "        input: select\n",
    "        label: Select collateral assets\n",
    "        multi: True\n",
    "        choices: ['CBETH (coinbase-wrapped-staked-eth)', 'RETH (rocket-pool)', 'SFRXETH (frax-ether)', 'SETH2 (stakewise)', 'ANKRETH (ankr)', 'USDC (flux-finance)', 'DAI (flux-finance)', 'USDT (flux-finance)', 'DAI-USDC-USDT (curve)', 'FRAX-USDC (curve)', 'FRAX-3CRV (curve)', 'LUSD-FRAXBP (convex-finance)', 'FRAX-3CRV (convex-finance)', 'FRAX-USDC (convex-finance)', 'DAI (compound)', 'USDC (compound)', 'WBTC (compound)', 'ETH (compound)', 'USDC (aave-v2)', 'DAI-USDC (uniswap-v3)', 'DAI-USDC (arrakis-finance)', 'MIM-3CRV (curve)', 'MIM-3CRV (convex-finance)', 'FRAX-USDC (uniswap-v3)', 'FPI-FRAX (frax)', 'USDC (goldfinch)', 'USDT (aave-v2)', 'USDT (compound)', 'USDC (morpho-aave)', 'DAI-USDC-USDT-SUSD (curve)', 'DAI (aave-v2)', 'WBTC (aave-v2)', 'ETH (aave-v2)', 'USDC-USDT (uniswap-v3)', 'DAI-USDC-USDT-SUSD (convex-finance)', 'LUSD-3CRV (curve)', 'TUSD-3CRV (curve)', 'TUSD-3CRV (convex-finance)', 'USDC (euler)', 'DOLA-FRAXBP (curve)', 'DOLA-FRAXBP (convex-finance)', 'USDC-EURS (curve)', 'USDC-EURS (convex-finance)', 'OUSD-3CRV (curve)', 'OUSD-3CRV (convex-finance)', 'USDC (compound-v3)', 'DAI-USDC (uniswap-v2)', 'ALUSD-FRAXBP (curve)', 'ALUSD-3CRV (curve)', 'ALUSD-3CRV (convex-finance)', 'DAI (morpho-compound)', 'USDT (euler)', 'DAI-USDC-USDT (convex-finance)', 'NUSDC (notional)', 'BEAN-3CRV (curve)', 'USDC (morpho-compound)', 'DAI (uwu-lend)', 'BUSD-USDC (uniswap-v3)', 'ADAI-AUSDC-AUSDT (curve)', 'CDAI-CUSDC (curve)', 'DAI-FRAX (uniswap-v3)', 'stETH (lido)', 'ETH-STETH (curve)', 'ETH-STETH (convex-finance)', 'WSTETH-WETH (balancer)', 'WSTETH-WETH (aura)', 'USDT-WBTC-WETH (curve)', 'USDT-WBTC-WETH (convex)', 'USDC (flux)', 'USDC (morpho)', 'USDC (compound-v3)', 'eUSD-FRAXBP (convex)', 'USDT (morpho)', 'sDAI (maker)']\n",
    "    reference_token:\n",
    "        input: select\n",
    "        label: Select reference asset\n",
    "        choices: ['CBETH (coinbase-wrapped-staked-eth)', 'RETH (rocket-pool)', 'SFRXETH (frax-ether)', 'SETH2 (stakewise)', 'ANKRETH (ankr)', 'USDC (flux-finance)', 'DAI (flux-finance)', 'USDT (flux-finance)', 'DAI-USDC-USDT (curve)', 'FRAX-USDC (curve)', 'FRAX-3CRV (curve)', 'LUSD-FRAXBP (convex-finance)', 'FRAX-3CRV (convex-finance)', 'FRAX-USDC (convex-finance)', 'DAI (compound)', 'USDC (compound)', 'WBTC (compound)', 'ETH (compound)', 'USDC (aave-v2)', 'DAI-USDC (uniswap-v3)', 'DAI-USDC (arrakis-finance)', 'MIM-3CRV (curve)', 'MIM-3CRV (convex-finance)', 'FRAX-USDC (uniswap-v3)', 'FPI-FRAX (frax)', 'USDC (goldfinch)', 'USDT (aave-v2)', 'USDT (compound)', 'USDC (morpho-aave)', 'DAI-USDC-USDT-SUSD (curve)', 'DAI (aave-v2)', 'WBTC (aave-v2)', 'ETH (aave-v2)', 'USDC-USDT (uniswap-v3)', 'DAI-USDC-USDT-SUSD (convex-finance)', 'LUSD-3CRV (curve)', 'TUSD-3CRV (curve)', 'TUSD-3CRV (convex-finance)', 'USDC (euler)', 'DOLA-FRAXBP (curve)', 'DOLA-FRAXBP (convex-finance)', 'USDC-EURS (curve)', 'USDC-EURS (convex-finance)', 'OUSD-3CRV (curve)', 'OUSD-3CRV (convex-finance)', 'USDC (compound-v3)', 'DAI-USDC (uniswap-v2)', 'ALUSD-FRAXBP (curve)', 'ALUSD-3CRV (curve)', 'ALUSD-3CRV (convex-finance)', 'DAI (morpho-compound)', 'USDT (euler)', 'DAI-USDC-USDT (convex-finance)', 'NUSDC (notional)', 'BEAN-3CRV (curve)', 'USDC (morpho-compound)', 'DAI (uwu-lend)', 'BUSD-USDC (uniswap-v3)', 'ADAI-AUSDC-AUSDT (curve)', 'CDAI-CUSDC (curve)', 'DAI-FRAX (uniswap-v3)', 'stETH (lido)', 'ETH-STETH (curve)', 'ETH-STETH (convex-finance)', 'WSTETH-WETH (balancer)', 'WSTETH-WETH (aura)', 'USDT-WBTC-WETH (curve)', 'USDT-WBTC-WETH (convex)', 'USDC (flux)', 'USDC (morpho)', 'USDC (compound-v3)', 'eUSD-FRAXBP (convex)', 'USDT (morpho)', 'sDAI (maker)']\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "711ab712",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import requests as req\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "29b6f635",
   "metadata": {},
   "outputs": [],
   "source": [
    "pool_dict = {\n",
    "    'CBETH (coinbase-wrapped-staked-eth)': '0f45d730-b279-4629-8e11-ccb5cc3038b4',\n",
    "    'RETH (rocket-pool)': 'd4b3c522-6127-4b89-bedf-83641cdcd2eb',\n",
    "    'SFRXETH (frax-ether)': '77020688-e1f9-443c-9388-e51ace15cc32',\n",
    "    'SETH2 (stakewise)': '66958f46-1d06-4f83-9fab-bbec354049d8',\n",
    "    'ANKRETH (ankr)': 'e201dbed-63fa-48e2-bfa2-f56e730167d2',\n",
    "    'USDC (flux-finance)': 'fa4d7ee4-0001-4133-9e8d-cf7d5d194a91',\n",
    "    'DAI (flux-finance)': 'ed227286-abb0-4a34-ada5-39f7ebd81afb',\n",
    "    'USDT (flux-finance)': '6600934f-6323-447d-8a7d-67fbede8529d',\n",
    "    'DAI-USDC-USDT (curve)': '25171c4c-1877-449a-9f88-45a9f153ee31',\n",
    "    'FRAX-USDC (curve)': '3f6aa14f-eb0c-4738-bf74-8bc666f7d2b1',\n",
    "    'FRAX-3CRV (curve)': '8d989d6c-99ba-447e-8f3d-3aca98e993fd',\n",
    "    'LUSD-FRAXBP (convex-finance)' : 'c3b238b8-e1b8-43a5-8079-99a73f3dc981',\n",
    "    'FRAX-3CRV (convex-finance)': '844a8a29-4653-42e6-b675-a6b43fac3678',\n",
    "    'FRAX-USDC (convex-finance)': 'bd072651-d99c-4154-aeae-51f12109c054',\n",
    "    'DAI (compound)': 'cc110152-36c2-4e10-9c12-c5b4eb662143',\n",
    "    'USDC (compound)': 'cefa9bb8-c230-459a-a855-3b94e96acd8c',\n",
    "    'WBTC (compound)': '1d876729-4445-4623-8b6b-c5290db5d100',\n",
    "    'ETH (compound)': '1e5da7c6-59bb-49bd-9f97-4f4fceeffad4',\n",
    "    'USDC (aave-v2)': 'a349fea4-d780-4e16-973e-70ca9b606db2',\n",
    "    'DAI-USDC (uniswap-v3)': '26298be5-691a-42e6-817b-07f72e70cd4f',\n",
    "    'DAI-USDC (arrakis-finance)': '2431aeec-d0b9-4e62-ab5e-ff8718ad45fc',\n",
    "    'MIM-3CRV (curve)': 'fb6676ba-0a45-44c8-86f6-63956956ebe1',\n",
    "    'MIM-3CRV (convex-finance)': '8a20c472-142c-4442-b724-40f2183c073e',\n",
    "    'FRAX-USDC (uniswap-v3)': 'd371fc69-9a77-4336-a129-ec79c9548266',\n",
    "    'FPI-FRAX (frax)': 'a61791ea-2886-4428-991c-7181d26a6062',\n",
    "    'USDC (goldfinch)': 'c89af47f-032a-4c59-bdc9-17a7f1514a3b',\n",
    "    'USDT (aave-v2)': '60d657c9-5f63-4771-a85b-2cf8d507ec00',\n",
    "    'USDT (compound)': '57647093-2868-4e65-97ab-9cae8ec74e7d',\n",
    "    'USDC (morpho-aave)': '325ad2d6-70b1-48d7-a557-c2c99a036f87',\n",
    "    'DAI-USDC-USDT-SUSD (curve)': '985b3a44-495f-4250-bde3-7b2299036e3e',\n",
    "    'DAI (aave-v2)': '405d8dad-5c99-4c91-90d3-82813ade1ff1',\n",
    "    'WBTC (aave-v2)': '40e0d8b7-5eba-4d6c-a3c2-9ac375bcd4bf',\n",
    "    'ETH (aave-v2)': 'f2726d05-1f8d-4b9c-80e3-43d03d85d117',\n",
    "    'USDC-USDT (uniswap-v3)': 'e737d721-f45c-40f0-9793-9f56261862b9',\n",
    "    'DAI-USDC-USDT-SUSD (convex-finance)': '45f74ed5-5832-4d6d-8f2c-2929b6ac5e9c',\n",
    "    'LUSD-3CRV (curve)': '836e7def-cb99-46f6-8e22-1056a81e4040',\n",
    "    'TUSD-3CRV (curve)': '0023d0df-b295-4bca-9e4f-12053445460f',\n",
    "    'TUSD-3CRV (convex-finance)': 'fde2777a-952a-49bd-b0be-b28bd35b7718',\n",
    "    'USDC (euler)': '61b7623c-9ac2-4a73-a748-8db0b1c8c5bc',\n",
    "    'DOLA-FRAXBP (curve)': '3a745337-3f04-409d-9627-8391e3c7494d',\n",
    "    'DOLA-FRAXBP (convex-finance)': 'd05cb04d-f1e5-451d-95a2-6a3a9da001ad',\n",
    "    'USDC-EURS (curve)': '4dbfda50-4474-4ef1-9f59-b5cf5ad7413c',\n",
    "    'USDC-EURS (convex-finance)': 'efa8dc4f-03df-4633-95bf-db188292d9a3',\n",
    "    'OUSD-3CRV (curve)': '4fcac035-f39c-4238-bc87-4c4cfe0b3092',\n",
    "    'OUSD-3CRV (convex-finance)': '9e038028-8f56-449f-8410-64683f0c086b',\n",
    "    'USDC (compound-v3)': '7da72d09-56ca-4ec5-a45f-59114353e487',\n",
    "    'DAI-USDC (uniswap-v2)': 'a86ee795-54d9-4812-9148-b312967cefe5',\n",
    "    'ALUSD-FRAXBP (curve)': '71a56b67-3123-4820-a30f-fac238de441c',\n",
    "    'ALUSD-3CRV (curve)': 'fa1ea651-4d34-4672-837f-9dcd043319b9',\n",
    "    'ALUSD-3CRV (convex-finance)': 'f11aa021-e4c1-49f9-8004-9cf5625dedae',\n",
    "    'DAI (morpho-compound)': '1e6a12f5-687c-4ce6-8416-af38f17954ea',\n",
    "    'USDT (euler)': '618c5e6c-78f3-4e20-9182-b16e5ef20292',\n",
    "    'DAI-USDC-USDT (convex-finance)': '7394f1bc-840a-4ff0-9e87-5e0ef932943a',\n",
    "    'NUSDC (notional)': '7131b94d-a801-446c-9968-8fa7f68b3b87',\n",
    "    'BEAN-3CRV (curve)': '3e2dbffc-b5b9-4d93-8236-46969f83d64b',\n",
    "    'USDC (morpho-compound)': 'b718e8ee-c749-4152-9f3d-e3f9ff2da564',\n",
    "    'DAI (uwu-lend)': '45a43ff6-9320-4e40-9812-ba91d6f39307',\n",
    "    'BUSD-USDC (uniswap-v3)': 'daef836d-0e55-41ba-81fc-335234eef50e',\n",
    "    'ADAI-AUSDC-AUSDT (curve)': 'e3f861c0-c2b9-4b50-b799-a036a3f11da1',\n",
    "    'CDAI-CUSDC (curve)': '8ec9e3e2-1eb5-4c47-82de-edcc825ca4cc',\n",
    "    'DAI-FRAX (uniswap-v3)': 'd6e3dd14-0495-4aec-b226-ae98215dcd38',\n",
    "    'stETH (lido)' : '747c1d2a-c668-4682-b9f9-296708a3dd90',\n",
    "    'ETH-STETH (curve)': '57d30b9c-fc66-4ac2-b666-69ad5f410cce',\n",
    "    'ETH-STETH (convex-finance)': '5ce23e7e-3800-4c9c-ad30-6db3db0515a1',\n",
    "    'WSTETH-WETH (balancer)': '4cc5df76-f81d-49fe-9e1e-4caa6a8dad0b',\n",
    "    'WSTETH-WETH (aura)': '6429fd3b-af61-4e15-a4b4-34819fb8f4ea',\n",
    "    'USDT-WBTC-WETH (curve)': '9e4dbe67-f5fc-4428-8e6f-93d464f40a0d',\n",
    "    'USDT-WBTC-WETH (convex)': 'ad3d7253-fb8f-402f-a6f8-821bc0a055cb',\n",
    "    'USDC (flux)': 'fa4d7ee4-0001-4133-9e8d-cf7d5d194a91',\n",
    "    'USDC (morpho)': '325ad2d6-70b1-48d7-a557-c2c99a036f87',\n",
    "    'USDC (compound-v3)': '7da72d09-56ca-4ec5-a45f-59114353e487',\n",
    "    'eUSD-FRAXBP (convex)': 'c04005c9-7e34-41a6-91c4-295834ed8ac0',\n",
    "    'USDT (morpho)': '1343a280-7812-4bc3-8f98-d1c37e11d271',\n",
    "    'sDAI (maker)': 'c8a24fee-ec00-4f38-86c0-9f6daebc4225'\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "61fbaa21",
   "metadata": {
    "id": "61fbaa21"
   },
   "outputs": [],
   "source": [
    "# Raw pool data in dictionaries \n",
    "\n",
    "pool_dict_raw = dict(pd.DataFrame(req.get('https://yields.llama.fi/pools').json())['data'])\n",
    "\n",
    "# Dataframe of raw data\n",
    "df_raw = pd.DataFrame.from_dict(pool_dict_raw, orient='index')\n",
    "df_raw = df_raw.sort_values(by ='tvlUsd', ascending = False)\n",
    "eth_pools = df_raw[df_raw.chain == 'Ethereum']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "13522a10",
   "metadata": {
    "id": "13522a10",
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Set Parameters for Basket\n",
    "\n",
    "min_apy = 0\n",
    "is_stablecoin = True\n",
    "min_tvl = 80000000\n",
    "top_x = 15\n",
    "sort_by = 'apy' # or tvlUsd or apy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cfe6871c",
   "metadata": {},
   "outputs": [],
   "source": [
    "basket_tokens = []\n",
    "reference_token = \"USDC (Compound)\"\n",
    "basket_weights = \"\"\n",
    "is_custom_weights = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "53875aff",
   "metadata": {},
   "outputs": [],
   "source": [
    "using_custom_weights = is_custom_weights and len(basket_tokens) == len(basket_weights.split(','))\n",
    "\n",
    "benchmark = pool_dict[reference_token]\n",
    "bespoke = [pool_dict[token] for token in basket_tokens]\n",
    "weights = [float(weight) if using_custom_weights else 0 for weight in basket_weights.split(',')]\n",
    "normalized_weights = [weight/sum(weights) for weight in weights if using_custom_weights]\n",
    "\n",
    "pool_symbols = eth_pools[eth_pools.pool.isin(bespoke)][['project','symbol','pool', 'tvlUsd','apy']]\n",
    "benchmark_symbols = eth_pools[eth_pools.pool == benchmark][['project','symbol','pool', 'tvlUsd','apy']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e4b2e6b",
   "metadata": {
    "id": "7e4b2e6b"
   },
   "outputs": [],
   "source": [
    "# Creates a table with pool symbol and pool ids to be later used for joining \n",
    "\n",
    "def symbol_ops(df):\n",
    "    # calc for income\n",
    "    df['income'] = df.tvlUsd * df.apy\n",
    "\n",
    "    # calc for income weighted basket based on current TVL and APY \n",
    "    df['income_basket_weight'] = round(df.income / sum(df.income),2)\n",
    "        \n",
    "    # concat the pool symbol to show pool and protocol\n",
    "    df['pool (protocol)'] = df.symbol + \" (\" + df.project + \")\"\n",
    "\n",
    "    #drop columns that we no longer need\n",
    "    df= df.drop(['tvlUsd','apy','income'], axis=1)\n",
    "    \n",
    "    return df\n",
    "    \n",
    "\n",
    "# Establishes a list of dataframes of historical data for each of the pools in the desired basket\n",
    "# Input is the dataframe returned by symbol_ops() \n",
    "\n",
    "def create_historical_dfs(df):\n",
    "    basket_pool_ids = list(df.pool)\n",
    "    \n",
    "    pool_dfs = []\n",
    "    for i in basket_pool_ids:\n",
    "        data = pd.DataFrame()\n",
    "        data = pd.DataFrame(req.get('https://yields.llama.fi/chart/'+ str(i)).json()['data'])\n",
    "        data = data[['timestamp','tvlUsd','apy']]\n",
    "        data['timestamp'] = [i[0:10] for i in list(data.timestamp)]\n",
    "        data['timestamp'] = pd.to_datetime(data.timestamp)\n",
    "        data['pool_id'] = str(i)\n",
    "\n",
    "        # joins pool symbol onto dataframe using pool id\n",
    "        data = pd.merge(data, df, how='left', \n",
    "             left_on= 'pool_id', right_on='pool' )[['timestamp','tvlUsd','apy','income_basket_weight','pool (protocol)']]\n",
    "\n",
    "        # adds column for portfolio yield contribution (apy * income_basket_weight)\n",
    "        data['portfolio_yield_contribution'] = data.iloc[:,2] * data.iloc[:,3]\n",
    "\n",
    "        # renames columns to reflect pool symbol and drops pool symbol column\n",
    "        pool_protocol_string = data['pool (protocol)'][0]\n",
    "        data.columns = ['timestamp',  \n",
    "                          ('tvlUsd | ' + pool_protocol_string), \n",
    "                           ('apy | ' + pool_protocol_string),\n",
    "                        'income_basket_weight | ' + pool_protocol_string,\n",
    "                        'pool (protocol)',\n",
    "                       'portfolio_yield_contribution | ' + pool_protocol_string]\n",
    "        data = data.drop('pool (protocol)', axis=1)\n",
    "\n",
    "        # creates and calculates column for income (apy column has more decimal points than shown, results in slight math discrepency on income)\n",
    "        #income_column_string = 'income | ' + pool_protocol_string\n",
    "        #data[income_column_string] = data.iloc[:, 1] * data.iloc[:, 2] / 100\n",
    "\n",
    "        pool_dfs.append(data)\n",
    "        \n",
    "    return pool_dfs\n",
    "\n",
    "\n",
    "#Checks to see which pool within the basket has the least amount of historical data\n",
    "# Input is the list of dfs returned by create_historical_dfs()\n",
    "def count_days_by_pool(pool_dfs_list):\n",
    "    for i in pool_dfs_list:\n",
    "        print( (list(i)[1][8:], ' : ', len(i)))\n",
    "\n",
    "\n",
    "        \n",
    "# Creates master dataframe with historical data froma all pools, using the pool that has the least hisory as base, \n",
    "# and caluculates the total_portfolio_yield for each day\n",
    "\n",
    "# Input is the list of dfs returned by create_historical_dfs()\n",
    "\n",
    "def calc_master_df(pool_dfs_list):\n",
    "    from functools import reduce\n",
    "    df_master = reduce(lambda x, y: pd.merge(x, y, on = 'timestamp', how ='left'), sorted(pool_dfs_list, key=len))\n",
    "    \n",
    "    yield_contribution_cols = [col for col in df_master.columns if 'portfolio_yield_contribution |' in col]\n",
    "\n",
    "    # caluculates the total_portfolio_yield for each day\n",
    "    df_master['total_portfolio_yield'] = df_master[yield_contribution_cols].sum(axis=1)\n",
    "    \n",
    "    return df_master"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1ebd1f8",
   "metadata": {
    "id": "e1ebd1f8"
   },
   "outputs": [],
   "source": [
    "pool_symbols = symbol_ops(pool_symbols)\n",
    "if(using_custom_weights):\n",
    "    pool_symbols['income_basket_weight'] = normalized_weights\n",
    "    \n",
    "benchmark_symbols = symbol_ops(benchmark_symbols)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "c271df56",
   "metadata": {},
   "source": [
    "## RToken Basket Composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c49bb33",
   "metadata": {},
   "outputs": [],
   "source": [
    "pool_symbols"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "813e005e",
   "metadata": {},
   "source": [
    "## Benchmark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "494e0663",
   "metadata": {},
   "outputs": [],
   "source": [
    "benchmark_symbols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f356e96f",
   "metadata": {},
   "outputs": [],
   "source": [
    "pool_dfs_basket = create_historical_dfs(pool_symbols)\n",
    "pool_dfs_benchmark = create_historical_dfs(benchmark_symbols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bec2d7af",
   "metadata": {
    "id": "bec2d7af"
   },
   "outputs": [],
   "source": [
    "df = calc_master_df(pool_dfs_basket)\n",
    "\n",
    "df_benchmark = calc_master_df(pool_dfs_benchmark)\n",
    "\n",
    "# makes basket and benchmark dataframes the same length\n",
    "num_days_of_data = min(len(df),len(df_benchmark))\n",
    "\n",
    "df = df.tail(num_days_of_data)\n",
    "df_benchmark = df_benchmark.tail(num_days_of_data)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "731da372",
   "metadata": {},
   "source": [
    "## Backtest Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88f36a2f",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 370
    },
    "id": "88f36a2f",
    "outputId": "66c7e782-53c6-4d25-ca18-4fae5e459b19"
   },
   "outputs": [],
   "source": [
    "_ = sns.lineplot(x = \"timestamp\", y = \"total_portfolio_yield\",\n",
    "             data = df)\n",
    "_ = sns.lineplot(x = \"timestamp\", y = \"total_portfolio_yield\",\n",
    "                data = df_benchmark, color=\"orange\")\n",
    "_ = plt.title('Benchmark Yield Over Time')\n",
    "_ = plt.ylabel('APY')\n",
    "_ = plt.xlabel('Date')\n",
    "_ = plt.legend(['RToken Basket Yield','Benchmark'])\n",
    "_ = plt.xticks(rotation = 45)\n"
   ]
  }
 ],
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